Alain Verbeke and Wenlong Yuan
The aim of this paper is to investigate how multinational enterprise (MNE) subsidiary capabilities are influenced by the firm-specific advantages (FSAs) of the parent company, as…
Abstract
Purpose
The aim of this paper is to investigate how multinational enterprise (MNE) subsidiary capabilities are influenced by the firm-specific advantages (FSAs) of the parent company, as well as by cultural and geographic distance between the home and host country.
Design/methodology/approach
This paper assesses how the effects of the parent FSAs, cultural distance and geographic distance on subsidiary capabilities vary for different value-chain activities, with an empirical application to 60 foreign subsidiaries operating in Canada.
Findings
This paper uncovers distinct, three-way interaction effects among parent-level FSAs, cultural distance and geographic distance for upstream versus downstream activities in the value chain.
Originality/value
We find that in special cases, high levels of distance can be positive for MNEs, in terms of driving the creation of stronger subsidiary capabilities.
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Wenzhou Wang, Zhe Shen and Wenlong Yuan
The affordable loss (AL) heuristic, as one crucial sub-dimension of effectuation, delineates the maximum level of investment entrepreneurs are ready to lose in a worst-case…
Abstract
Purpose
The affordable loss (AL) heuristic, as one crucial sub-dimension of effectuation, delineates the maximum level of investment entrepreneurs are ready to lose in a worst-case scenario. Conflicting conceptualizations remain regarding whether entrepreneurs’ psychological traits matter for AL. Based on the narcissistic admiration and narcissistic rivalry perspective, this study investigates the relationship between chief executive officer (CEO) narcissism and AL behaviors.
Design/methodology/approach
Using data collected from the CEOs and paired vice presidents at 122 small and medium enterprises (SMEs) in mainland China, the authors intend to further explore the association between psychological traits, especially CEO narcissism and AL behaviors under environment and resource constraints (e.g. perceived uncertainty and slack resources).
Findings
The findings show that CEO admiration-based narcissism is positively related to AL behaviors in the firm. Furthermore, when firms hold more slack resources, narcissistic admiration has a stronger positive association with AL; while when the environment becomes more uncertain, narcissistic admiration has a weaker positive association with AL. In contrast, CEO rivalry-based narcissism is negatively related to AL behaviors in the firm. When the environment becomes more uncertain, narcissistic rivalry has a stronger negative association with AL.
Originality/value
This article contributes to trait-based effectuation research and suggests that individual psychological traits affect AL behaviors at the firm level, though the patterns of the relationship vary with both the type of narcissism and contexts.
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Bradley J. Olson, Satyanarayana Parayitam, Matteo Cristofaro, Yongjian Bao and Wenlong Yuan
This paper elucidates the role of anger in error management (EM) and organizational learning behaviors. The study explores how anger can catalyze learning, emphasizing its…
Abstract
Purpose
This paper elucidates the role of anger in error management (EM) and organizational learning behaviors. The study explores how anger can catalyze learning, emphasizing its strategic implications.
Design/methodology/approach
A double-layered moderated-mediated model was developed and tested using data from 744 Chinese CEOs. The psychometric properties of the survey instrument were rigorously examined through structural equation modeling, and hypotheses were tested using Hayes's PROCESS macros.
Findings
The findings reveal that anger is a precursor for recognizing the value of significant errors, leading to a positive association with learning behavior among top management team members. Additionally, the study uncovers a triple interaction effect of anger, EM culture and supply chain disruptions on the value of learning from errors. Extensive experience and positive grieving strengthen the relationship between recognizing value from errors and learning behavior.
Originality/value
This study uniquely integrates affect-cognitive theory and organizational learning theory, examining anger in EM and learning. The authors provide empirical evidence that anger can drive error value recognition and learning. The authors incorporate a more fine-grained approach to leadership when including executive anger as a trigger to learning behavior. Factors like experience and positive grieving are explored, deepening the understanding of emotions in learning. The authors consider both negative and positive emotions to contribute to the complexity of organizational learning.
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Alain Verbeke and Wenlong Yuan
This paper proposes a new typology of Ownership (O) advantages as a function of their differential managerial implications in established multinational enterprises (MNEs). We…
Abstract
This paper proposes a new typology of Ownership (O) advantages as a function of their differential managerial implications in established multinational enterprises (MNEs). We argue that the mainstream typology of O advantages proposed in Dunning’s eclectic paradigm does not recognize the uniqueness of individual firms. We therefore propose a new typology of O advantages, which distinguishes among four types, based on the geographic source of such advantages and their transferability across borders. Moreover, we acknowledge the importance of resource recombination advantages. Two case examples illustrate the implications of the new typology for established MNEs.
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“First principles” of international business (IB) thinking should be applied systematically when assessing the functioning of internationally operating firms. The most important…
Abstract
“First principles” of international business (IB) thinking should be applied systematically when assessing the functioning of internationally operating firms. The most important first principle is that entrepreneurially oriented firms seek to create, deliver and capture economic value through cross-border linkages. Such linkages invariably require complementary resources from a variety of parties with idiosyncratic vulnerabilities to be meshed. Starting from first principles allows bringing to light evidence-based insight. For instance, most companies are not global and even the world’s largest firms rarely change the location of key strategic functions. International new ventures (INVs), emerging economy multinational enterprises (MNEs) and family firms face unique vulnerabilities but also command resources that can be used to create value across borders. The quest for “optimal” international diversification appears to be a futile academic exercise, and in emerging economies with institutional voids, relational networks – and more broadly, informal institutions – are unlikely to function as scalable substitutes for formal institutions. In global value chains (GVCs), many lead firms and their partners have been able to craft governance mechanisms that reduce bounded rationality and bounded reliability challenges, and it is also critical for them to use governance as a tool to create entrepreneurial space. Finally, many of the world’s largest companies have been on successful trajectories toward reducing their climate change footprint for a few decades. But these firm-specific trajectories are fraught with challenges and cannot just be imposed via unilateral, macro-level targets decided upon by individuals and institutions lacking a clear understanding of innovation and capital expenditure processes in business.
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Chiara Mio, Andrea Venturelli and Rossella Leopizzi
The purpose of this paper is to examine the relationship between remuneration for the achievement of objectives and sustainability, and – more specifically – the amount of…
Abstract
Purpose
The purpose of this paper is to examine the relationship between remuneration for the achievement of objectives and sustainability, and – more specifically – the amount of attention that listed companies in Italy devote to defining, and consequently to communicating externally, sustainability as a criterion in establishing the wage levels of managers and directors.
Design/methodology/approach
It was decided to ascertain whether the quality of information regarding sustainability provided in connection with the remuneration policies of listed companies tallies with the general quality of information regarding sustainability provided through companies’ main (obligatory and voluntary) reporting procedures.
Findings
The results of this research show that the inconsistency between the information provided in voluntary and obligatory reports (between reports on sustainability and remuneration reports) extends to the levels of information provided in the two types of obligatory report (the reports on remuneration and on management); there is also a discrepancy between the levels of information provided in these reports and the evaluation of that information by an external assessor.
Research limitations/implications
One of the limitations of this research is that as the data examined were gleaned from public documents, it is not necessarily an accurate reflection of all the information that firms have at their disposal on questions of sustainability and remuneration policies. The existence of internal documents containing other information, and therefore leading to different results, cannot be ruled out.
Originality/value
This study is the first in Italy to examine the question of how limited companies report issues relating to management by objectives-corporate social responsibility. It does this through the introduction of a mixed system for ESG information, which counteracts the subjective limitations of the internal evaluation provided by the research group by adding in the authoritative evaluations of an external assessor.
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Jian Mou, Wenlong Zhu and Morad Benyoucef
The purpose of this paper is to investigate the impact of product description and involvement on purchase intention in a cross-border e-commerce (CBEC) setting from a…
Abstract
Purpose
The purpose of this paper is to investigate the impact of product description and involvement on purchase intention in a cross-border e-commerce (CBEC) setting from a psychological perspective.
Design/methodology/approach
This study proposes a research model of purchase intention in CBEC based on the involvement theory and commitment-involvement theory. The research model was tested using the covariance-based structural equation modeling technique. Data were collected from consumers on a popular CBEC platform in China.
Findings
A high-quality product description has no significant positive effect on purchase intention, but it has significant positive effects on product cognitive involvement, product affective involvement, platform enduring involvement and platform situational involvement. In addition, product affective involvement, platform enduring involvement and platform situational involvement all have significant positive effect on purchase intention, but this effect is not significant in the relationship between product cognitive involvement and purchase intention.
Practical implications
This study calls for sellers to optimize product descriptions on CBEC platforms in order to attract more buyers and generate more profits.
Originality/value
This study integrates two theories of involvement into the research model in the CBEC context. Based on this model, the authors analyzed how product description affects purchase intention under the joint influence of two involvement factors.
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This study aims to address the challenge of automatic guided vehicle (AGV) scheduling for parcel storage and retrieval in an intelligent warehouse.
Abstract
Purpose
This study aims to address the challenge of automatic guided vehicle (AGV) scheduling for parcel storage and retrieval in an intelligent warehouse.
Design/methodology/approach
This study presents a scheduling solution that aims to minimize the maximum completion time for the AGV scheduling problem in an intelligent warehouse. First, a mixed-integer linear programming model is established, followed by the proposal of a novel genetic algorithm to solve the scheduling problem of multiple AGVs. The improved algorithm includes operations such as the initial population optimization of picking up goods based on the principle of the nearest distance, adaptive crossover operation evolving with iteration, mutation operation of equivalent exchange and an algorithm restart strategy to expand search ability and avoid falling into a local optimal solution. Moreover, the routing rules of AGV are described.
Findings
By conducting a series of comparative experiments based on the actual package flow situation of an intelligent warehouse, the results demonstrate that the proposed genetic algorithm in this study outperforms existing algorithms, and can produce better solutions for the AGV scheduling problem.
Originality/value
This paper optimizes the different iterative steps of the genetic algorithm and designs an improved genetic algorithm, which is more suitable for solving the AGV scheduling problem in the warehouse. In addition, a path collision avoidance strategy that matches the algorithm is proposed, making this research more applicable to real-world scheduling environments.
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Zhenghao Liu, Yuxing Qian, Wenlong Lv, Yanbin Fang and Shenglan Liu
Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news…
Abstract
Purpose
Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.
Design/methodology/approach
This study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.
Findings
Experimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.
Originality/value
The study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.
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This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.
Abstract
Purpose
This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.
Design/methodology/approach
In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.
Findings
The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.
Originality/value
In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.